Magneto: Unified fine-grained path control in legacy and openflow Hybrid Networks

Cheng Jin; Cristian Lumezanu; Qiang Xu; Hesham Mekky; Zhi-Li Zhang; Guofei Jiang

doi:10.1145/3050220.3050229

Magneto: Unified fine-grained path control in legacy and openflow Hybrid Networks

Cheng Jin, Cristian Lumezanu, Qiang Xu, Hesham Mekky, Zhi-Li Zhang, Guofei Jiang

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

28 Scopus citations

Abstract

Software-defined networking (SDN) provides fine-grained network control and monitoring that simplifies network management. Unfortunately, upgrading existing enterprise networks, comprised of numerous "legacy" switches, to SDN is often cost-prohibitive. We argue that it is possible to achieve most of the benefits of a fully deployed SDN at a fraction of the cost by strategically replacing only few legacy switches with - or introducing a few - new SDN-capable switches in a legacy network, thus creating a hybrid network. We present Magneto, a unified network controller that exerts SDN-like, fine-grained path control over both OpenFlow and legacy switches in hybrid networks. Magneto i) introduces magnet MAC addresses and dynamically updates IPto-magnet MAC mappings at hosts via gratuitous ARP messages for visibility and routing control; and ii) uses the ability of SDN switches to send "custom" packets into the data plane to manipulate legacy switches into updating forwarding entries with magnet MAC addresses for enhanced routing flexibility. Our evaluation on a lab testbed and through extensive simulations on large enterprise network topologies show that Magneto is able to achieve full control over routing when only 20% of network switches are programmable, with negligible computation and latency overhead.

Original language	English (US)
Title of host publication	SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research
Publisher	Association for Computing Machinery, Inc
Pages	75-87
Number of pages	13
ISBN (Electronic)	9781450349475
DOIs	https://doi.org/10.1145/3050220.3050229
State	Published - Apr 3 2017
Event	2017 Symposium on SDN Research, SOSR 2017 - Santa Clara, United States Duration: Apr 3 2017 → Apr 4 2017

Publication series

Name	SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research

Other

Other	2017 Symposium on SDN Research, SOSR 2017
Country/Territory	United States
City	Santa Clara
Period	4/3/17 → 4/4/17

Bibliographical note

Funding Information:
This research was supported in part by NSF grants CNS-1411636, CNS 1618339 and CNS 1617729, DTRA grant HDTRA1-14-1-0040 and DoD ARO MURI Award W911NF-12-1-0385.

Publisher Copyright:
© 2017 ACM.

Keywords

Hybrid SDN
MAC learning and forwarding
Magneto

Publisher link

10.1145/3050220.3050229

Find It

Find It at U of M Libraries

Cite this

Jin, C., Lumezanu, C., Xu, Q., Mekky, H., Zhang, Z.-L., & Jiang, G. (2017). Magneto: Unified fine-grained path control in legacy and openflow Hybrid Networks. In SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research (pp. 75-87). (SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research). Association for Computing Machinery, Inc. https://doi.org/10.1145/3050220.3050229

Magneto: Unified fine-grained path control in legacy and openflow Hybrid Networks. / Jin, Cheng; Lumezanu, Cristian; Xu, Qiang et al.
SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research. Association for Computing Machinery, Inc, 2017. p. 75-87 (SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jin, C, Lumezanu, C, Xu, Q, Mekky, H, Zhang, Z-L & Jiang, G 2017, Magneto: Unified fine-grained path control in legacy and openflow Hybrid Networks. in SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research. SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research, Association for Computing Machinery, Inc, pp. 75-87, 2017 Symposium on SDN Research, SOSR 2017, Santa Clara, United States, 4/3/17. https://doi.org/10.1145/3050220.3050229

@inproceedings{b17b77b237cf4d7880f7bfaee7db9076,

title = "Magneto: Unified fine-grained path control in legacy and openflow Hybrid Networks",

abstract = "Software-defined networking (SDN) provides fine-grained network control and monitoring that simplifies network management. Unfortunately, upgrading existing enterprise networks, comprised of numerous {"}legacy{"} switches, to SDN is often cost-prohibitive. We argue that it is possible to achieve most of the benefits of a fully deployed SDN at a fraction of the cost by strategically replacing only few legacy switches with - or introducing a few - new SDN-capable switches in a legacy network, thus creating a hybrid network. We present Magneto, a unified network controller that exerts SDN-like, fine-grained path control over both OpenFlow and legacy switches in hybrid networks. Magneto i) introduces magnet MAC addresses and dynamically updates IPto-magnet MAC mappings at hosts via gratuitous ARP messages for visibility and routing control; and ii) uses the ability of SDN switches to send {"}custom{"} packets into the data plane to manipulate legacy switches into updating forwarding entries with magnet MAC addresses for enhanced routing flexibility. Our evaluation on a lab testbed and through extensive simulations on large enterprise network topologies show that Magneto is able to achieve full control over routing when only 20% of network switches are programmable, with negligible computation and latency overhead.",

keywords = "Hybrid SDN, MAC learning and forwarding, Magneto",

author = "Cheng Jin and Cristian Lumezanu and Qiang Xu and Hesham Mekky and Zhi-Li Zhang and Guofei Jiang",

note = "Funding Information: This research was supported in part by NSF grants CNS-1411636, CNS 1618339 and CNS 1617729, DTRA grant HDTRA1-14-1-0040 and DoD ARO MURI Award W911NF-12-1-0385. Publisher Copyright: {\textcopyright} 2017 ACM.; 2017 Symposium on SDN Research, SOSR 2017 ; Conference date: 03-04-2017 Through 04-04-2017",

year = "2017",

month = apr,

day = "3",

doi = "10.1145/3050220.3050229",

language = "English (US)",

series = "SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research",

publisher = "Association for Computing Machinery, Inc",

pages = "75--87",

booktitle = "SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research",

}

TY - GEN

T1 - Magneto

T2 - 2017 Symposium on SDN Research, SOSR 2017

AU - Jin, Cheng

AU - Lumezanu, Cristian

AU - Xu, Qiang

AU - Mekky, Hesham

AU - Zhang, Zhi-Li

AU - Jiang, Guofei

N1 - Funding Information: This research was supported in part by NSF grants CNS-1411636, CNS 1618339 and CNS 1617729, DTRA grant HDTRA1-14-1-0040 and DoD ARO MURI Award W911NF-12-1-0385. Publisher Copyright: © 2017 ACM.

PY - 2017/4/3

Y1 - 2017/4/3

N2 - Software-defined networking (SDN) provides fine-grained network control and monitoring that simplifies network management. Unfortunately, upgrading existing enterprise networks, comprised of numerous "legacy" switches, to SDN is often cost-prohibitive. We argue that it is possible to achieve most of the benefits of a fully deployed SDN at a fraction of the cost by strategically replacing only few legacy switches with - or introducing a few - new SDN-capable switches in a legacy network, thus creating a hybrid network. We present Magneto, a unified network controller that exerts SDN-like, fine-grained path control over both OpenFlow and legacy switches in hybrid networks. Magneto i) introduces magnet MAC addresses and dynamically updates IPto-magnet MAC mappings at hosts via gratuitous ARP messages for visibility and routing control; and ii) uses the ability of SDN switches to send "custom" packets into the data plane to manipulate legacy switches into updating forwarding entries with magnet MAC addresses for enhanced routing flexibility. Our evaluation on a lab testbed and through extensive simulations on large enterprise network topologies show that Magneto is able to achieve full control over routing when only 20% of network switches are programmable, with negligible computation and latency overhead.

AB - Software-defined networking (SDN) provides fine-grained network control and monitoring that simplifies network management. Unfortunately, upgrading existing enterprise networks, comprised of numerous "legacy" switches, to SDN is often cost-prohibitive. We argue that it is possible to achieve most of the benefits of a fully deployed SDN at a fraction of the cost by strategically replacing only few legacy switches with - or introducing a few - new SDN-capable switches in a legacy network, thus creating a hybrid network. We present Magneto, a unified network controller that exerts SDN-like, fine-grained path control over both OpenFlow and legacy switches in hybrid networks. Magneto i) introduces magnet MAC addresses and dynamically updates IPto-magnet MAC mappings at hosts via gratuitous ARP messages for visibility and routing control; and ii) uses the ability of SDN switches to send "custom" packets into the data plane to manipulate legacy switches into updating forwarding entries with magnet MAC addresses for enhanced routing flexibility. Our evaluation on a lab testbed and through extensive simulations on large enterprise network topologies show that Magneto is able to achieve full control over routing when only 20% of network switches are programmable, with negligible computation and latency overhead.

KW - Hybrid SDN

KW - MAC learning and forwarding

KW - Magneto

UR - http://www.scopus.com/inward/record.url?scp=85018983058&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85018983058&partnerID=8YFLogxK

U2 - 10.1145/3050220.3050229

DO - 10.1145/3050220.3050229

M3 - Conference contribution

AN - SCOPUS:85018983058

T3 - SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research

SP - 75

EP - 87

BT - SOSR 2017 - Proceedings of the 2017 Symposium on SDN Research

PB - Association for Computing Machinery, Inc

Y2 - 3 April 2017 through 4 April 2017

ER -

Magneto: Unified fine-grained path control in legacy and openflow Hybrid Networks

Abstract

Publication series

Other

Bibliographical note

Keywords

Publisher link

Find It

Other files and links

Fingerprint

Cite this